CAKE (Cascading and Adaptive KV cache Eviction) intelligently manages memory resources across LLM layers by treating cache eviction as a "cake-slicing problem" - allocating different resources based on each layer's unique attention patterns.

• Layer-specific optimization - Recognizes different attention patterns across model layers
• Resource allocation - Slices the "memory cake" more efficiently than one-size-fits-all approaches
• Memory efficiency - Reduces inference bottlenecks when processing long sequences
• Adaptive design - Dynamically adjusts based on layer preferences and attention behaviors

For engineering teams, CAKE represents a practical advancement in LLM memory management that can improve throughput and enable longer context processing without hardware upgrades.

CAKE: Cascading and Adaptive KV Cache Eviction with Layer Preferences